Evidence map›Paper›PMID 32025648›Full record

ArticleJAMIA open2019

A semi-automated pipeline for fulfillment of resource requests from a longitudinal Alzheimer's disease registry.

Katelyn A McKenzie, Suzanne L Hunt, Genevieve Hulshof, Dinesh Pal Mudaranthakam, Kayla Meyer, Eric D Vidoni, Jeffrey M Burns, Jonathan D Mahnken

Open access · goldAbstract read
In one paragraph

Article in JAMIA open, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 38% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 2 institutions in 1 country.

Katelyn A McKenzieDepartment of Biostatistics, University of Kansas Medical Center, Kansas City, Kansas, USA.ORCID 0000-0002-8784-0509
Suzanne L HuntDepartment of Biostatistics, University of Kansas Medical Center, Kansas City, Kansas, USA.
Genevieve HulshofDepartment of Biostatistics, University of Kansas Medical Center, Kansas City, Kansas, USA.
Dinesh Pal MudaranthakamDepartment of Biostatistics, University of Kansas Medical Center, Kansas City, Kansas, USA.
Kayla MeyerUniversity of Kansas Alzheimer's Disease Center, Fairway, Kansas, USA.
Eric D VidoniUniversity of Kansas Alzheimer's Disease Center, Fairway, Kansas, USA.
Jeffrey M BurnsUniversity of Kansas Alzheimer's Disease Center, Fairway, Kansas, USA.
Jonathan D MahnkenDepartment of Biostatistics, University of Kansas Medical Center, Kansas City, Kansas, USA.
University of Kansas · USUniversity of Kansas Medical Center · US

Funding

University of Kansas Alzheimer's Disease Research Center (KU ADRC)P30AG072973 · NIA · UNIVERSITY OF KANSAS MEDICAL CENTER · PI JEFFREY Murray BURNS, RUSSELL H. SWERDLOW · 2021 to 2026
$25.3M
University of Kansas Alzheimer's Disease Core CentersP30AG035982 · NIA · UNIVERSITY OF KANSAS MEDICAL CENTER · PI SWERDLOW, RUSSELL H. · 2011 to 2020
$16.6M
NIA NIH HHS P30 AG035982NIA NIH HHS P30 AG072973
6 · The paper itself

Abstract

objectiveManaging registries with continual data collection poses challenges, such as following reproducible research protocols and guaranteeing data accessibility. The University of Kansas (KU) Alzheimer's Disease Center (ADC) maintains one such registry: Curated Clinical Cohort Phenotypes and Observations (C3PO). We created an automated and reproducible process by which investigators have access to C3PO data. MATERIALS AND

methodsData was input into Research Electronic Data Capture. Monthly, data part of the Uniform Data Set (UDS), that is data also collected at other ADCs, was uploaded to the National Alzheimer's Coordinating Center (NACC). Quarterly, NACC cleaned, curated, and returned the UDS to the KU Data Management and Statistics (DMS) Core, where it was stored in C3PO with other quarterly curated site-specific data. Investigators seeking to utilize C3PO submitted a research proposal and requested variables via the publicly accessible and searchable data dictionary. The DMS Core used this variable list and an automated SAS program to create a subset of C3PO.

resultsC3PO contained 1913 variables stored in 15 datasets. From 2017 to 2018, 38 data requests were completed for several KU departments and other research institutions. Completing data requests became more efficient; C3PO subsets were produced in under 10 seconds. DISCUSSION: The data management strategy outlined above facilitated reproducible research practices, which is fundamental to the future of research as it allows replication and verification to occur.

conclusionWe created a transparent, automated, and efficient process of extracting subsets of data from a registry where data was changing daily.

Indexed as

dynamic dataNational Alzheimer’s Coordinating Centerreproducible researchresearch data management

Identifiers

PMID32025648
PMCPMC6993996
OpenAlexW2970890530

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.